I’m an operations leader with a hands-on technical background and experience across construction, manufacturing, defence and asset-heavy businesses.

My work has covered the commercial and operational sides of running businesses and projects — people, delivery, estimating and margin, budgeting and forecasting, procurement, assets, safety, quality and business systems.

This GitHub is an extension of that work.

Most of the projects here started with an operating problem I had encountered directly: deciding which work to pursue, identifying which project needs intervention, understanding whether people and equipment are actually ready, testing an investment under uncertainty, or finding where a supply network is most exposed.

I focus on making operating decisions that are normally spread across experience, spreadsheets and disconnected systems easier to see, explain and act on.

Together, these projects cover a connected set of management decisions: what work to pursue, where delivery is at risk, whether resources are ready, whether an investment survives uncertainty, and where supply could fail first.

Should we commit scarce estimating, working-capital and delivery capacity to this opportunity — and what would change the answer?

A commercial pursuit-governance system for specialty contractors combining hard risk gates, attractiveness and winnability, margin and expected value, cash and capacity exposure, uncertainty, approval and override controls, and outcome calibration.

Built from an estimating qualification process I developed in commercial construction. In the broader operating improvement effort, estimating rework fell 30%, average margin improved 8%, major-bid throughput increased from roughly one every two weeks to 2–4 per week, and small-bid turnaround moved from 2–4 days to hours–1 day. The public application is a later portfolio implementation, not the source of those operating results.

Live demo · Management case study · Decision memo

Does an investment still make sense when the assumptions move?

A decision-support engine for capital and operating decisions using scenario modelling, Monte Carlo simulation, NPV, breakeven, DSCR, sensitivity analysis and stress testing.

Which project needs attention today, and why?

A portfolio view of construction job-cost, schedule, billing, change-order, margin and compliance risk designed to surface the problems that need intervention rather than produce another report.

Are the people, equipment, permits and compliance actually ready for tomorrow’s work?

A field-operations system connecting workforce availability, equipment, maintenance, permits, inspections, compliance and weather into a single job-readiness view.

If part of the supply network fails, when do we stop shipping — and what is the best mitigation?

A supply-chain resilience simulator built around disruption scenarios, time-to-survive, time-to-recover and mitigation decisions.

Can a mapped biological connectome produce useful navigation behaviour in simulation?

An experimental simulation project using a fruit-fly connectome as an agent controller and comparing its behaviour with conventional navigation models.

I’m also developing Mulligan Hills, a larger private project in Godot involving deterministic simulation, persistent world state, mobile interaction and interconnected management systems.

It gives me a different kind of problem to work on: maintaining architecture, testing and product coherence as a system becomes substantially larger and more interconnected.

The subject matter changes, but the approach is fairly consistent:

Understand the operation → identify the real constraint → make the assumptions visible → build the simplest useful system → test the result → improve it

The test is whether a system helps someone make a better decision, not whether it uses complicated technology.

That usually means the output needs to explain why, not simply show another metric:

• Why was the bid rejected?
• What assumption changes the investment decision?
• What is blocking tomorrow’s work?
• Which project needs intervention first?
• Where does the supply network fail?
• What evidence supports the result?

I use software, data and automation as tools for operational improvement rather than as ends in themselves.

For these portfolio projects, I remain responsible for the problem definition, operating logic, assumptions, system design, decision rules, validation and acceptance of the result.

One principle is consistent across the work:

Implemented is not the same as verified, and verified is not the same as production-ready.

Where something is experimental, incomplete or has not yet been validated in the real environment, it is identified as such.